Electrical Machines Diagnosis

Electrical Machines Diagnosis

Author: Jean-Claude Trigeassou

Publisher: John Wiley & Sons

Published: 2013-02-07

Total Pages: 268

ISBN-13: 1118601750

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Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives. This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit. Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is performed with a large variety of techniques: parameter estimation, state observation, Kalman filtering, spectral analysis, neural networks, fuzzy logic, artificial intelligence, etc. Particular emphasis in this book is put on the modeling of the electrical machine in faulty situations. Electrical Machines Diagnosis presents original results obtained mainly by French researchers in different domains. It will be useful as a guideline for the conception of more robust electrical machines and indeed for engineers who have to monitor and maintain electrical drives. As the monitoring and diagnosis of electrical machines is still an open domain, this book will also be very useful to researchers.


Fault Diagnosis of Induction Motors

Fault Diagnosis of Induction Motors

Author: Jawad Faiz

Publisher: IET

Published: 2017-08-29

Total Pages: 535

ISBN-13: 1785613286

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This book is a comprehensive, structural approach to fault diagnosis strategy. The different fault types, signal processing techniques, and loss characterisation are addressed in the book. This is essential reading for work with induction motors for transportation and energy.


Signal Processing and Analysis of Electrical Circuit

Signal Processing and Analysis of Electrical Circuit

Author: Adam Glowacz

Publisher: MDPI

Published: 2020-03-13

Total Pages: 604

ISBN-13: 3039282948

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This Special Issue with 35 published articles shows the significance of the topic “Signal Processing and Analysis of Electrical Circuit”. This topic has been gaining increasing attention in recent times. The presented articles can be categorized into four different areas: signal processing and analysis methods of electrical circuits; electrical measurement technology; applications of signal processing of electrical equipment; fault diagnosis of electrical circuits. It is a fact that the development of electrical systems, signal processing methods, and circuits has been accelerating. Electronics applications related to electrical circuits and signal processing methods have gained noticeable attention in recent times. The methods of signal processing and electrical circuits are widely used by engineers and scientists all over the world. The constituent papers represent a significant contribution to electronics and present applications that can be used in industry. Further improvements to the presented approaches are required for realizing their full potential.


Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems

Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems

Author: Mohamed Benbouzid

Publisher: IET

Published: 2020-12-09

Total Pages: 283

ISBN-13: 1785619578

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This book contains 5 chapters that discusses the following topics: Parametric signal processing approach; The signal demodulation techniques; Kullback-Leibler divergence for incipient fault diagnosis; Higher-order spectra and Fault detection and diagnosis based on principal component analysis.


Fault Diagnosis and Detection

Fault Diagnosis and Detection

Author: Mustafa Demetgul

Publisher: BoD – Books on Demand

Published: 2017-05-31

Total Pages: 338

ISBN-13: 9535132032

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Mass production companies have become obliged to reduce their production costs and sell more products with lower profit margins in order to survive in competitive market conditions. The complexity and automation level of machinery are continuously growing. This development calls for some of the most critical issues that are reliability and dependability of automatic systems. In the future, machines will be monitored remotely, and computer-aided techniques will be employed to detect faults in the future, and also there will be unmanned factories where machines and systems communicate to each other, detect their own faults, and can remotely intercept their faults. The pioneer studies of such systems are fault diagnosis studies. Thus, we hope that this book will contribute to the literature in this regard.


Proceedings of the 4th International Conference on Electrical Engineering and Control Applications

Proceedings of the 4th International Conference on Electrical Engineering and Control Applications

Author: Sofiane Bououden

Publisher: Springer Nature

Published: 2020-09-29

Total Pages: 1257

ISBN-13: 9811564035

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This book gathers papers presented during the 4th International Conference on Electrical Engineering and Control Applications. It covers new control system models, troubleshooting tips and complex system requirements, such as increased speed, precision and remote capabilities. Additionally, the papers discuss not only the engineering aspects of signal processing and various practical issues in the broad field of information transmission, but also novel technologies for communication networks and modern antenna design. This book is intended for researchers, engineers and advanced postgraduate students in the fields of control and electrical engineering, computer science and signal processing, as well as mechanical and chemical engineering.


Deep Learning Applications, Volume 2

Deep Learning Applications, Volume 2

Author: M. Arif Wani

Publisher: Springer Nature

Published: 2020-09-24

Total Pages: 307

ISBN-13: 981156759X

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This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.


Intelligent Production Machines and Systems - 2nd I*PROMS Virtual International Conference 3-14 July 2006

Intelligent Production Machines and Systems - 2nd I*PROMS Virtual International Conference 3-14 July 2006

Author: Duc T. Pham

Publisher: Elsevier

Published: 2011-07-28

Total Pages: 685

ISBN-13: 0080556345

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I*PROMS 2005 is an online web-based conference. It provides a platform for presenting, discussing, and disseminating research results contributed by scientists and industrial practitioners active in the area of intelligent systems and soft computing techniques (such as fuzzy logic, neural networks, evolutionary algorithms, and knowledge-based systems) and their application in different areas of manufacturing. Comprised of 100 peer-reviewed articles, this important resource provides tools to help enterprises achieve goals critical to the future of manufacturing.I*PROMS is an European Union-funded network that involves 30 partner organizations and more than 130 researchers from universities, research organizations, and corporations.* State-of-the-art research results * Leading European researchers and industrial practitioners * Comprehensive collection of indexed and peer-reviewed articles in book format supported by a user-friendly full-text CD-ROM with search functionality


Condition Monitoring with Vibration Signals

Condition Monitoring with Vibration Signals

Author: Hosameldin Ahmed

Publisher: John Wiley & Sons

Published: 2020-01-07

Total Pages: 456

ISBN-13: 1119544629

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Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoringguiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.